• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.211-225
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• 2011

In this paper, a class of bi-directional associative memory (BAM) fuzzy cellular neural networks with distributed delays and impulses is formulated and investigated. By employing an integro-differential inequality with impulsive initial conditions and the topological degree theory, some sufficient conditions ensuring the existence and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with distributed delays are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on the delay kernel functions and system parameters. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.582-585
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• 2001

Requirements for device networks differ greatly from those of data(business) networks. Consequently, any control network technology which uses a fieldbus protocol is, in general, different from IP network protocol TCP/IP. One needs to integrate fieldbus protocol and TCP/IP to realize distributed control over IP network or internet. This paper suggests a basic concept that can be applied to distributed control over IP network or internet. Specifically, LonWorks technology that uses LonTalk protocol is reviewed as device network. LonWorks technology provides networked intelligent I/O and controllers which make it a powerful, expandable solution. It is also addressed that many hardwired PLCs can be replaced by LonWorks devices. Connecting these remote LonWorks networks to the Internet can provide a powerful, integrated, distributed control system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3421-3425
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• 2015

In sensor networks, sensor nodes are usually distributed to manage the networks in continuous unique area, however as by the network property nodes can be located in several areas. The data gathering of distributed nodes to several areas can be different with current continuous area. Hence, the distributed networks can be differently managed to the current continuous networks. In this paper, we describe the data gathering of sensor nodes in distributed sensor areas. It is possible that sensor nodes cannot instantly connect the mobile sink, and the node operation should be considered. The real time data sending to the instant connection scheme of mobile sink can be implemented, but the property of mobile sink should be considered for the sink connection of distributed areas. In this paper, we analyze the proposed scheme by the simulation results. The simulation results show that the overall lifetime to the periodic data gathering method is longer than the threshold method.

• Smart Structures and Systems
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• v.19 no.4
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• pp.383-391
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• 2017

In this paper, we investigate the impacts of network topology on the performance of a distributed estimation algorithm, namely combine-then-adaptive (CTA) diffusion LMS, based on the data with or without the assumptions of temporal and spatial independence with noisy links. The study covers different network models, including the regular, small-world, random and scale-free whose the performance is analyzed according to the mean stability, mean-square errors, communication cost (link density) and robustness. Simulation results show that the noisy links do not cause divergence in the networks. Also, among the networks, the scale free network (heterogeneous) has the best performance in the steady state of the mean square deviation (MSD) while the regular is the worst case. The robustness of the networks against the issues like node failure and noisier node conditions is discussed as well as providing some guidelines on the design of a network in real condition such that the qualities of estimations are optimized.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.11
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• pp.986-992
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• 2012

In order to support quickly increasing mobile traffic and deal with various types of users of wireless mobile systems under overlay convergent cognitive networking environments, it is highly required to improve the performance and the capability of the wireless access networks. With distributed antennas and distributed processors, it is possible for mobile terminals (MTs) to monitor interference and control system effectively to minimize mutual interference among users and cells. Virtual cell changes as the MT moves or the environment changes, so no handoff is needed in connections with base station hotelling. In this paper, the characteristics of wireless distributed systems under the overlay convergent networks will be investigated.

• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.577-594
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• 2013

In this paper, we study the global stability and the existence of almost periodic solution of high-order Hopfield neural networks with distributed delays of neutral type. Some sufficient conditions are obtained for the existence, uniqueness and global exponential stability of almost periodic solution by employing fixed point theorem and differential inequality techniques. An example is given to show the effectiveness of the proposed method and results.

• Journal of the Korean Mathematical Society
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• v.43 no.2
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• pp.445-459
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• 2006

In this paper cellular neural networks with continuously distributed delays are considered. Sufficient conditions for the existence and exponential stability of the almost periodic solutions are established by using fixed point theorem, Lyapunov functional method and differential inequality technique. The results of this paper are new and they complement previously known results.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.327-330
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• 2003

This paper proposes an estimation algorithm for the generating power of distributed generations(DG) interconnected with distribution networks. These days, DG are rapidly increasing and most of them are interconnected with distribution networks. The DG can supply power into the distribution network, which may make significant impact on fault current and the protection scheme of the interconnected distribution networks. Generally these influences of DG is proportioned as the distributed generator's power. Therefore, it is important to forecast the output power of distributed generator in PCC(point of common coupling). This paper presents the prediction method of DG's power by monitoring the current and phase difference.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1405-1412
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• 2000

In this paper, we propose an efficient dynamic wavelength assignment algorithm in distributed WDM (Wavelength-Division Multiplexing) networks without wavelength conversion. The algorithm tries to assign a locally-most-used wavelength distributedly on a fixed routing path. We first formulate our algorithm by using the concept of a sample space which consists of optical fibers connected to nodes on a routing path of a lightpath to be assigned a wavelength. In particular, we analyze the blocking performance mathematically as compared with that of the most-used (MU) wavelength assignment algorithm previously proposed for WDM networks under centralized control. We also obtain numerical results by simulation on the blocking performance of other centralized/distributed wavelength assignment algorithms as well as our algorithm using the M/M/c/c dynamic traffic model. Consequently, we show that analytical results match simulation results and that our algorithm is efficient in distributed WDM networks in terms of blocking performance, control traffic overhead and computation complexity.

• Journal of KIISE
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• v.41 no.11
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• pp.958-966
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• 2014

Wireless sensor networks offer a distributed processing environment. Many sensor nodes are deployed in fields that have limited resources such as computing power, network bandwidth, and electric power. The sensor nodes construct their own networks automatically, and the collected data are sent to the sink node. In these traditional wireless sensor networks, network congestion due to packet flooding through the networks shortens the network life time. Clustering or in-network technologies help reduce packet flooding in the networks. Many studies have been focused on saving energy in the sensor nodes because the limited available power leads to an important problem of extending the operation of sensor networks as long as possible. However, we focus on the execution time because clustering and local distributed processing already contribute to saving energy by local decision-making. In this paper, we present a cooperative processing model based on the processing timeline. Our processing model includes validation of the processing, prediction of the total execution time, and determination of the optimal number of processing nodes for distributed processing in wireless sensor networks. The experiments demonstrate the accuracy of the proposed model, and a case study shows that our model can be used for the distributed application.